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Medium

3Sum

A medium Arrays problem included in Apna College, Love Babbar 450, Striver A2Z. Below: the roles whose interviews prioritise this topic, and how to practise it.

Topic
Arrays
Sheets
3
Core for
25 roles
Platform
LeetCode

The problem

Given an integer array, find all unique triplets [nums[i], nums[j], nums[k]] with distinct indices that sum up to zero.

Example 1

Input
nums = [-1,0,1,2,-1,-4]
Output
[[-1,-1,2],[-1,0,1]]
Why
The distinct index triplets [-1,-1,2] and [-1,0,1] each sum to 0 with no duplicate sets.

Example 2

Input
nums = [0,1,1]
Output
[]
Why
No combination of three numbers sums up to zero.

Example 3

Input
nums = [0,0,0]
Output
[[0,0,0]]
Why
The three zeros sum to 0 and form the single unique valid triplet.

Constraints

  • 3 <= nums.length <= 3000
  • -10^5 <= nums[i] <= 10^5

How to think about it

Updated 2026-09-09

Fixing one number turns the problem into finding two numbers in the remaining suffix that sum to -nums[i]. Sorting the array organizes duplicate values next to each other, allowing two pointers to sweep inward while skipping identical adjacent values to guarantee that every generated triplet is unique.

Approaches, worst first

  1. Triple nested loops with set deduplication

    time O(n^3) · space O(n)

    Iterate through all index triplets (i, j, k) with three nested loops, verify whether their sum is 0, sort the matched triplet, and insert it into a set to weed out duplicates. Extremely slow at cubic time and consumes significant memory for set overhead.

  2. Hash set complement lookup

    time O(n^2) · space O(n)

    Fix nums[i], then for the remaining elements maintain a hash set of visited values to find -nums[i] - nums[j]. Avoids the third loop, but still requires post-processing or set hashing to filter duplicate value combinations.

  3. Sort, then two-pointer scanWrite this one

    time O(n^2) · space O(1)

    Sort the array ascending. Iterate i from 0 to n - 3, skipping nums[i] == nums[i - 1]. Use two pointers low = i + 1 and high = n - 1 to find pairs summing to -nums[i]. On a match, record the triplet and advance past all identical neighbor values on both ends.

Where people lose marks · 3
  • Failing to skip duplicate values for the outer loop variable i, which generates duplicate triplet solutions.
  • Skipping duplicates only on one pointer instead of both left and right after recording a valid triplet.
  • Terminating the inner two-pointer search after the first match rather than continuing to search for other valid pairs with the same outer element.

Full solution

Sort, then fix one number and two-pointer scan the rest for the complement sum — O(n^2) time, O(1) extra space, and the sorted order makes duplicate-triplet skipping trivial on both pointers.

Python
from typing import List


def three_sum(nums: List[int]) -> List[List[int]]:
    nums.sort()
    n = len(nums)
    result = []
    for i in range(n - 2):
        if i > 0 and nums[i] == nums[i - 1]:
            continue  # skip duplicate anchors
        if nums[i] > 0:
            break  # smallest remaining value is positive, no zero sum possible
        low, high = i + 1, n - 1
        while low < high:
            total = nums[i] + nums[low] + nums[high]
            if total < 0:
                low += 1
            elif total > 0:
                high -= 1
            else:
                result.append([nums[i], nums[low], nums[high]])
                low += 1
                high -= 1
                while low < high and nums[low] == nums[low - 1]:
                    low += 1
                while low < high and nums[high] == nums[high + 1]:
                    high -= 1
    return result
JavaScript
function threeSum(nums) {
  nums = [...nums].sort((a, b) => a - b);
  const n = nums.length;
  const result = [];
  for (let i = 0; i < n - 2; i++) {
    if (i > 0 && nums[i] === nums[i - 1]) continue; // skip duplicate anchors
    if (nums[i] > 0) break; // smallest remaining value is positive, no zero sum possible
    let low = i + 1;
    let high = n - 1;
    while (low < high) {
      const total = nums[i] + nums[low] + nums[high];
      if (total < 0) {
        low++;
      } else if (total > 0) {
        high--;
      } else {
        result.push([nums[i], nums[low], nums[high]]);
        low++;
        high--;
        while (low < high && nums[low] === nums[low - 1]) low++;
        while (low < high && nums[high] === nums[high + 1]) high--;
      }
    }
  }
  return result;
}
Try it in the editor

The theory behind it

Arrays — the ground this problem stands on. All Arrays problems

What Arrays is

An array is a row of fixed boxes laid side by side in computer memory, like numbered lockers in a hallway. Because each box occupies identical space and sits directly next to its neighbors, jumping to locker zero or locker ten thousand takes the exact same tiny fraction of time. Every box holds an item of the same type, addressed by an offset number called an index.

When to reach for it

Reach for an array when items arrive in a known sequence and need immediate retrieval by position number. Problems asking for running totals, prefix accumulations, cyclic rotations, or in-place rearrangements signal array mechanics. Whenever constraints require constant-time random lookups or contiguous cache scans across fixed collections, a flat sequence is the default container.

How the pattern works

Visualize a tape with zero-indexed slots stretching from start to end. Keep track of write and read cursors when modifying contents without allocating helper buffers. For running computations, maintain an invariant such as having processed all elements left of the current index while pending elements wait to the right. When modifying entries in place, consider scanning backwards from the end so unread data is not overwritten.

What each operation costs

OperationTime
look up element by indexO(1)
insert or delete at the startO(n)
search an unsorted collection for a valueO(n)
What usually goes wrong with Arrays
  • Reading past the final index by checking index less than or equal to length instead of strictly less than length, triggering index out of bounds exceptions.
  • Modifying length or removing elements during a forward iteration loop, which causes remaining items to shift left and skip validation on the next neighbor.
  • Assuming dynamic resizing is costless inside nested loops, causing repeated memory reallocation copies when appending unknown quantities of items.

Which roles need this problem

Arrays is a core topic for these 25 roles — if you're targeting one of them, this problem is early in your path, not optional.

Secondary for 3 more roles, including Database Engineer, Bioinformatics Engineer, Networking Engineer.

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